Thumbnail Image
Publication

Optimizing genetic algorithm parameters for atmospheric carbon monoxide modeling

Duggal, Meera
; 
Hammerling, Dorit
Citations
Altmetric:
Advisor
Editor
Date
2021
Date Issued
Date Submitted
Keywords
genetic algorithms
 carbon monoxide modeling
Collections
Reuleaux 2021
Show all metadata
Files
Thumbnail Image
Reuleaux_2021_Duggal_Hammerling_Optimizing-Genetic-Algorithm-Parameters.pdf
Adobe PDF, 1.33 MB
Research Projects
Organizational Units
Journal Issue
URI
https://hdl.handle.net/11124/178560
 https://doi.org/10.25676/11124/178560
Embargo Expires
Abstract
Climate indices can measure the variability in the climate such as changes in sea surface temperature and wind. With this knowledge a predictive CO model was developed (Buchholz et al., 2018). This model uses climate indices to predict future CO emissions which are directly linked to large burn events that will occur in the southern hemisphere. We use four different climate indices in our model: the El Nino Southern Oscillation in the central tropical Pacific region 3.4, Indian Ocean Dipole/Dipole Mode Index (IOD/DMI), Tropical South Atlantic Index (TSA), and the Antartic [sic] Oscillation Index (AAO).
Associated Publications
Rights
Creative Commons CC-BY License or the Creative Commons CC-BY-NC License.
Embedded videos